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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Discovery of Stable Surfaces with Extreme Work Functions by High‐Throughput Density Functional Theory and Machine Learning

Abstract The work function is the key surface property that determines the energy required to extract an electron from the surface of a material. This property is crucial for thermionic energy conversion, band alignment in heterostructures, and electron emission devices. This work presents a high‐throughput workflow using density functional theory (DFT) to calculate the work function and cleavage energy of 33,631 slabs (58,332 work functions) that are created from 3,716 bulk materials. The number of calculated surface properties surpasses the previously largest database by a factor of ≈27. Several surfaces with an ultra‐low (<2 eV) and ultra‐high (>7 eV) work function are identified. Specifically, the (100)‐Ba‐O surface of BaMoO 3 and the (001)‐F surface of Ag 2 F have record‐low (1.25 eV) and record‐high (9.06 eV) steady‐state work functions. Based on this database a physics‐based approach to featurize surfaces is utilized to predict the work function. The random forest model achieves a test mean absolute error (MAE) of 0.09 eV, comparable to the accuracy of DFT. This surrogate model enables rapid predictions of the work function (≈ 10 5 faster than DFT) across a vast chemical space and facilitates the discovery of material surfaces with extreme work functions for energy conversion and electronic device applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Porous Polymers as Universal Reversal Agents for Heparin Anticoagulants through an Inclusion–Sequestration Mechanism

Heparins are widely used anticoagulants for surgical procedures and extracorporeal therapies. However, all of them have bleeding risks. Protamine sulfate, the only clinically approved antidote for unfractionated heparin (UFH), has adverse effects. Moreover, protamine can only partially neutralize low-molecular-weight heparins (LMWHs) and is not effective for fondaparinux. In this report an inclusion–sequestration strategy for efficient neutralization of heparin anticoagulants by cationic porous supramolecular organic frameworks (SOFs) and porous organic polymers (POPs) is reported. Isothermal titration calorimetric and fluorescence experiments show strong binding affinities of these porous polymers toward heparins, whereas dynamic light scattering and zeta potential analysis confirm that the heparin sequences are adsorbed into the interior of the porous hosts. Activated partial thromboplastin time, anti-FXa, and thromboelastography assays indicate that their neutralization efficacies are higher than or as high as that of protamine for UFH and generally superior to protamine for LMWHs and fondaparinux, which is further confirmed by tail-transection model in mice and ex vivo aPTT or anti-FXa analysis in rats. Acute toxicity evaluations reveal that one of the SOFs displays outstanding biocompatibility. This work suggests that porous polymers can supply safe and rapid reversal of clinically used heparins, as protamine surrogates, providing an improved approach for their neutralization.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Material-Dependent Antagonistic Effects between Soot and ZDDP

While soot in engine oil is known to accelerate the wear of diesel and gasoline direct-injection compression-ignition engines, there is a lack of consensus on the wear mechanism though various hypotheses have been proposed in the literature. Particularly, some recently observed antagonistic effects between soot and a common lubricant antiwear additive, zinc dialkyldithiophosphate (ZDDP), while others did not. The discrepancy is, in part, explained by the strong alloy dependence of such antagonism discovered in this study. Specifically, four alloys, 52100 steel and M2, M50, and A2 tool steels, are tested in lubricants containing carbon black (CB, a soot surrogate) with and without ZDDP present. Adding the CB alone to the oil increases the wear rate for all steel alloys as expected. However, distinct wear performance is observed for the four steel alloys when ZDDP is introduced to the CB-containing oil: while the 52100 steel has notable wear reduction, the three tool steels suffer significant wear increase. Comprehensive tribofilm characterization suggests that the Mo content in the steel alloy and the sulfur from ZDDP strongly influence wear behavior. The combination of CB/Mo-catalyzed sulfidation and CB-accelerated abrasion is hypothesized to be responsible for the high wear of the Mo-alloyed tool steels.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Wide‐Field Bond Quality Evaluation Using Frequency Domain Thermoreflectance with Deep Neural Network Feature Reconstruction

Heterogeneous integration of microelectronic components provides a pathway to improve circuit/component performance; however, this comes with assembly challenges, in particular due to complex interfaces via subsurface bump bonds. The ability of these bonds to transmit electrical signals and conduct heat to the carrier substrate limits component performance. In this work, hyperspectral frequency‐domain thermoreflectance (FDTR) imaging is demonstrated as a robust technique for evaluating the quality of subsurface indium bump bonds in a surrogate microelectronic sample. By performing microscale FDTR imaging with coarse motion image stitching, thermal phase maps that cover a 4 mm by 4 mm field‐of‐view with subsurface feature sensitivity at depths greater than 50 µm are obtained. The resulting FDTR hyperspectral data contains more than three million pixels and reveal the quality of subsurface microbump arrays. Wide‐field analysis of bonded versus gap regions is enabled by deep neural network feature reconstruction, that after training, rapidly provides an interpretable representation of bond quality. Utility of noisy higher frequency FDTR phase maps, i.e., near the computationally predicted sensing depth limit, results in an average prediction error of 11%. Taken together, FDTR with neural network‐based analysis demonstrates subsurface bond monitoring at length scales relevant for heterogeneously integrated microelectronics.

FDTR↗
DOE OSTI2022

Accelerated Discovery of CH 4 Uptake Capacity Metal–Organic Frameworks Using Bayesian Optimization

Abstract High‐throughput computational studies for discovery of metal–organic frameworks (MOFs) for separations and storage applications are often limited by the costs of computing thermodynamic quantities. Recent such studies at the time of writing may use ab initio results for a narrow selection of MOFs or empirical force‐field methods for larger selections. Here, a proof‐of‐concept study is conducted using Bayesian optimization on CH 4 uptake capacity of hypothetical MOFs for an existing dataset (Wilmer et al., Nature Chem. 2012, 4 , 83). It is shown that less than 0.1% of the database needs to be screened with the Bayesian optimization approach to recover the top candidate MOFs. This opens the possibility for efficient screening of MOF databases using accurate ab initio calculations for future adsorption studies on a minimal subset of MOFs. Furthermore, Bayesian optimization and the surrogate model presented here can offer interpretable material design insights and the framework will be applicable in the context of other target properties.

Taw, Eric↗
DOE OSTI2023

Na 3 Zr 2 Si 2 PO 12 Solid Electrolyte Membrane for High‐Performance Seawater Battery

Abstract Seawater batteries (SWBs) have gained tremendous interest in the electrochemical energy storage research field because of their low cost, natural abundance, and potential use for long‐duration energy storage. Advancing a SWB to demonstration projects is plagued by the poor electrochemical performance stemming from the poor interfaces of the solid electrolyte (SE), as well as the structural and chemical instabilities and sluggish ionic transport properties. In this study, the anode compartment of a surrogate SWB is constructed with a Na | SE | hard carbon configuration, and tailored dopants are introduced into the Nasicon‐type Na 3 Zr 2 Si 2 PO 12 (NZSP) SE membrane. After doping with TiO 2 , a much more densely packed pellet with uniformly distributed porous structure is obtained. Changes in surface chemistry and local structure in the bulk are observed, which are believed to contribute to the improved ionic conductivity and higher critical current density of the TiO 2 ‐doped NZSP. Stable cycling performance with reversible capacities based on different Na storage mechanisms are also demonstrated.

25 ENERGY STORAGE↗
DOE OSTI2020

Modeling and simulation of gas separations with spiral–wound membranes

Models for gas separations with spiral–wound membranes are developed and found to exhibit good agreement with experiments performed on N 2 /O 2 mixtures. The two–dimensional (2D) model can be accurately approximated by a one–dimensional (1D) surrogate model when the spacer widths are chosen to make the channel pressure drops small. Subsequently, the separation of propane/propylene mixtures from the recycle purge stream of a polypropylene reactor is investigated. Assuming ideal gas is found to lead to significant overestimations in membrane stage cuts (sometimes more than 10%), an extent comparable to that associated with extrapolating constant olefin permeance from a low–pressure condition. While olefin permeance can change significantly with pressure, using a constant–permeance formulation can result in a small (< 2.5%) underprediction in stage cut if the value for the permeance is taken from the feed condition. Finally, membrane properties and costs necessary for a viable separation process are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

The influence of random packed column parameters on the liquid holdup and interfacial area

Abstract Carbon dioxide capture via solvent absorption in packed columns has emerged as a potential technology to mitigate coal‐fired power plant CO 2 emissions. Parameters, including packing types, solvent properties, and operating conditions, could potentially affect the packed column CO 2 capture efficiency. To understand the importance of those parameters and help packed column optimization, a design of experiments (DoEs) method was proposed to generate input parameter matrix. Combined with multiphase computational fluid dynamics (CFD), the random packed column parameter influence on the liquid holdup and interfacial area can be efficiently investigated. Surrogate‐based sensitivity analysis shows that the solvent flow rate and contact angle are key factors dictating liquid holdup and interfacial area. On the other hand, solvent viscosity has a marginal impact on the interfacial area. The sensitivity scores were calculated for each input parameter to guide the selection of dimensionless numbers for the liquid holdup and interfacial area correlation development.

42 ENGINEERING↗
DOE OSTI2023

Relaxing the constant molar overflow assumption in distillation optimization

Abstract The constant molar overflow (CMO) framework, while useful for shortcut distillation models, assumes that all components have the same latent heats of vaporization. A simple transformation, from molar flows to latent‐heat flows, allows shortcut models to retain the mathematical simplicity of the CMO framework while accounting for different latent heats, resulting in the constant heat transport (CHT) framework for adiabatic distillation columns. Although several past works have already proposed this transformation in the literature, it has not been well utilized in recent times. In this article, we show the utility of this transformation in upgrading various applications such as identifying energy‐efficient multicomponent distillation configurations based on heat duty rather than surrogate vapor flow. The method transforms the diagram to a diagram. Furthermore, we derive new and insightful analytical results in distillation, such as cumulative latent‐heat stage fractions having monotonic profiles within a distillation column under the CHT framework.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Investigating the influence of particle distribution on force and torque statistics using hierarchical machine learning

An accurate representation of hydrodynamic force and torque experienced by every particle in a distribution can be obtained from particle resolved (PR) simulations. These unique quantities are influenced by the deterministic position of surrounding particles. However, systems simulated with this methodology are typically limited to particles due to the involved computational cost. This resource requirement is a major bottleneck in analyzing the effect of variations in particle distribution. Here, this article attempts to address this bottleneck by availing relatively inexpensive deep learning models. The surrogate models that we employ in this article use a physics‐based hierarchical framework and symmetry‐preserving neural networks to achieve robustness with limited training data. This article first performs additional generalizability tests on PR data of distinct distributions that are not involved in the training process. The models are then deployed on several different particle distributions. Impact of clustering and structure on the observed statistics are investigated.

42 ENGINEERING↗
DOE OSTI2026

A Comprehensive Comparative Study of Active Learning Schemes for Nanophotonics Design

We present a benchmarking study of active learning (AL) schemes for designing planar multilayer nanophotonic metamaterials, where the design tasks are formulated as binary optimization problems. Different surrogate models, including factorization machine (FM), Gaussian process regression (GPR), and convolutional neural network (CNN), combined with different optimization methods, including exhaustive enumeration, discrete particle swarm optimization (DPSO), quantum annealing (QA), hybrid QA, and simulated annealing are studied. The benchmark cases investigated range from small problems with short binary lengths (N = 25) to large problems with N up to 100, focusing on the design of two classes of photonic structures, including antireflective coatings for the long-wavelength infrared region and transparent radiative coolers. For small problems, CNN coupled with DPSO in AL achieves the best performance. As N increases, FM with QA outperforms GPR and CNN. For FM-based AL, hybrid QA yields the best optimization results, particularly in high-dimensional cases (N = 100). These results demonstrate that the optimization method can significantly affect in AL performance as N increases, and that QA-based optimization can provide practical routes for mitigating the optimization bottleneck in high-dimensional problems.

Jung, Serang [Kyung Hee University, Korea]↗
DOE OSTI2025

Data‐Driven Insights into Rare Earth Mineralization: Machine Learning Applications Using Functional Material Synthesis Data

Understanding rare‐earth element (REE) mineralization mechanisms is essential for developing efficient separation strategies. Although the geochemical pathways that generate REE deposits are qualitatively known, quantitative links between specific conditions and mineralization outcomes remain limited. Herein, the repurpose laboratory REE hydrothermal synthesis data—originally collected for functional‐materials fabrication—as a surrogate for studying mineralization with data‐driven methods. The compiled 1,200+ hydrothermal reaction records and trained three machine‐learning models—K‐nearest neighbors (KNN), random forest (RF), and extreme gradient boosting (XGB)—to predict product elements and phases from precursors, additives, reaction conditions, and engineered features. Validation shows XGB achieves the highest accuracy. Feature importance indicates thermodynamic properties of cations and anions dominate model decisions. Correlations reveal positive relationships among precursor concentration, reaction time, pH, and temperature, consistent with classical crystallization behavior. XGB‐based regressors are built to predict crystallization temperature and pH from precursor/product attributes. Performance is strongest when similar training examples exist, while accuracy declines for underrepresented reactions, notably REE carbonates and heavy‐REE systems. Overall, the study shows that functional‐materials datasets can illuminate REE mineralization and provide priors for exploration and processing. Expanding datasets with less‐studied chemistries and conditions will improve generality and support deposit discovery and more efficient REE recovery.

feature importance analysis↗
DOE OSTI2022

Perovskite Photocatalytic CO 2 Reduction or Photoredox Organic Transformation?

Abstract Metal‐halide perovskites have been explored as photocatalysts for CO 2 reduction. We report that perovskite photocatalytic CO 2 reduction in organic solvents is likely problematic. Instead, the detected products (i.e., CO) likely result from a photoredox organic transformation involving the solvent. Our observations have been validated using isotopic labeling experiments, band energy analysis, and new control experiments. We designed a typical perovskite photocatalytic setup in organic solvents that led to CO production of up to ≈1000 μmol g −1 h −1 . CO 2 reduction in organic solvents must be studied with extra care because photoredox organic transformations can produce orders of magnitude higher rate of CO or CH 4 than is typical for CO 2 reduction routes. Though CO 2 reduction is not likely to occur, in situ CO generation is extremely fast. Hence a suitable system can be established for challenging organic reactions that use CO as a feedstock but exploit the solvent as a CO surrogate.

San Martin, Jovan↗
DOE OSTI2022

Static and Dynamic Gradient Based Directional Transportation of Neutral Molecules in Swollen Polymer Films

Abstract Materials which selectively transport molecules offer powerful opportunities for concentrating and separating chemical agents. Here, utilizing static and dynamic chemical gradients, transport of molecules within swollen crosslinked polymers is demonstrated. Using an ≈200 μm static hydroxyl to hexyl gradient, the neutral ambipolar nerve agent surrogate diethyl (cyanomethyl)phosphonate (DECP) is directionally transported and concentrated 60‐fold within 4 hours. To accelerate transport kinetics, a dynamic gradient (a “travelling wave”) is utilized. Here, the non‐polar dye pyrene was transported. The dynamic gradient is generated by an ion exchange process triggered by the localized introduction of an aqueous NaCl solution, which converts the gel from hydrophobic to hydrophilic. As the hydrophilic region expands, associated water enters the gel, and pyrene is pushed ahead of the expansion front. The dynamic gradient provides about 10‐fold faster transport kinetics than the static gradient.

Ali, Mohammad A.↗
DOE OSTI2022

Perovskite Photocatalytic CO 2 Reduction or Photoredox Organic Transformation?

Abstract Metal‐halide perovskites have been explored as photocatalysts for CO 2 reduction. We report that perovskite photocatalytic CO 2 reduction in organic solvents is likely problematic. Instead, the detected products (i.e., CO) likely result from a photoredox organic transformation involving the solvent. Our observations have been validated using isotopic labeling experiments, band energy analysis, and new control experiments. We designed a typical perovskite photocatalytic setup in organic solvents that led to CO production of up to ≈1000 μmol g −1 h −1 . CO 2 reduction in organic solvents must be studied with extra care because photoredox organic transformations can produce orders of magnitude higher rate of CO or CH 4 than is typical for CO 2 reduction routes. Though CO 2 reduction is not likely to occur, in situ CO generation is extremely fast. Hence a suitable system can be established for challenging organic reactions that use CO as a feedstock but exploit the solvent as a CO surrogate.

14 SOLAR ENERGY↗
DOE OSTI2022

Static and Dynamic Gradient Based Directional Transportation of Neutral Molecules in Swollen Polymer Films

Abstract Materials which selectively transport molecules offer powerful opportunities for concentrating and separating chemical agents. Here, utilizing static and dynamic chemical gradients, transport of molecules within swollen crosslinked polymers is demonstrated. Using an ≈200 μm static hydroxyl to hexyl gradient, the neutral ambipolar nerve agent surrogate diethyl (cyanomethyl)phosphonate (DECP) is directionally transported and concentrated 60‐fold within 4 hours. To accelerate transport kinetics, a dynamic gradient (a “travelling wave”) is utilized. Here, the non‐polar dye pyrene was transported. The dynamic gradient is generated by an ion exchange process triggered by the localized introduction of an aqueous NaCl solution, which converts the gel from hydrophobic to hydrophilic. As the hydrophilic region expands, associated water enters the gel, and pyrene is pushed ahead of the expansion front. The dynamic gradient provides about 10‐fold faster transport kinetics than the static gradient.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Expansion of the Na 3 M III (Ln/An) 6 F 30 Series: Incorporation of Plutonium into a Highly Robust and Stable Framework

Abstract Na n MAn 6 F 30 is an extremely versatile framework structure for incorporating tetravalent actinides (An) and cerium along with divalent or trivalent d‐metals (M); moreover, the structure exhibits a high resistance to harsh chemical conditions. This extreme robustness can potentially be exploited for the sequestration of plutonium in a stable matrix; however, no Na n MPu 6 F 30 compounds have been reported so far. Herein, we present four new plutonium fluorides that have been prepared as single crystals by mild hydrothermal synthesis methods. Structural characterizations revealed their compositions to be Na 3 AlPu 6 F 30 , Na 3 FePu 6 F 30 , Na 3 CoPu 6 F 30 , and Na 2.4 Mn 1.6 Pu 6 F 30 . Surprisingly, in the plutonium series, it was found that Co 2+ and Mn 2+ precursors oxidized to form Na 3 Co III Pu 6 F 30 and Na 2.4 Mn II/III 1.6 Pu 6 F 30 , whereas the analogous reactions for cerium result in reduction of the transition metal, even when beginning with a M 3+ precursor. While cerium is often used as a surrogate for plutonium, this work serves as an example that deviations between their chemistries do occur.

Pace, Kristen A.↗
DOE OSTI2023

Pertechnetate/perrhenate–capped Zr/Hf–Dihydroxide Dimers: Elucidating Zr–TcO 4 Co–Mobility in the Nuclear Fuel Cycle

Spent nuclear fuel contains heavy element fission products that must be separated for effective reprocessing for a safe and sustainable nuclear fuel cycle. 93 Zr and 99 Tc are high-yield fission products that co-transport in liquid-liquid extraction processes. Here we seek atomic-level information of this co-extraction process, as well as fundamental knowledge about Zr IV (and Hf IV ) aqueous speciation in the presence of topology-directing ligands such as pertechnetate (TcO 4 – ) and non-radioactive surrogate perrhenate (ReO 4 – ). In this context, we show that the flat tetrameric oxyhydroxyl-cluster [M IV 4 (OH) 8 (H 2 O) 16 ] 8+ (and related polymers) is dissociated by perrhenate/pertechnetate to yield isostructural dimers, M 2 (OH) 2 (XO 4 – ) 6 (H 2 O) 6 • 3H 2 O (M=Zr/Hf IV ; X=Re/Tc VII ), elucidated by single-crystal X-ray diffraction. We used these model compounds to understand the pervasive 93 Zr- 99 Tc coextraction with further speciation studies in water, nitric acid, and tetrabutylphosphate (TBP) -kerosene; where the latter two media are relevant to nuclear fuel reprocessing. SAXS (small angle X-ray scattering), compositional evaluation, and where experimentally feasible, ESI-MS (electrospray ionization mass spectrometry) showed that perrhenate/pertechnetate influence Zr/Hf IV -speciation in water. Here, in Zr-XO 4 solvent extraction studies to simulate fuel reprocessing, we provide evidence that TcO 4 – enhances extraction of Zr IV , and compositional analysis of the extracted metal-complexes (Zr-ReO 4 study) is consistent with the crystallized Zr IV 2 (OH) 2 (Re VII O 4 – ) 6 (H 2 O) 6 •dimer.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗